Cantitate/Preț
Produs
Total produse
Vezi coșul
Linear Models and the Relevant Distributions and Matrix Algebra: A Unified Approach Volume 2 de David A. Harville

Linear Models and the Relevant Distributions and Matrix Algebra: A Unified Approach Volume 2

Autor David A. Harville
en Limba Engleză Hardback – 23 oct 2023
Linear Models and the Relevant Distributions and Matrix Algebra: A Unified Approach, Volume 2 covers several important topics that were not included in the first volume. The second volume complements the first, providing detailed solutions to the exercises in both volumes, thereby greatly enhancing its appeal for use in advanced statistics programs. This volume can serve as a valuable reference. It can also serve as a resource in a mathematical statistics course for use in illustrating various theoretical concepts in the context of a relatively complex setting of great practical importance. Together with the first volume, this volume provides a largely self-contained treatment of an important area of statistics and should prove highly useful to graduate students and others.
Key Features:
  • Includes solutions to the exercises from both the first and second volumes
  • Includes coverage of several topics not covered in the first volume
  • Highly valuable as a reference book for graduate students and researchers
Citește tot Restrânge

Toate formatele și edițiile

Toate formatele și edițiile Preț Express
Paperback (1) 38762 lei  6-8 săpt.
  CRC Press – 30 iun 2020 38762 lei  6-8 săpt.
Hardback (1) 69982 lei  6-8 săpt.
  CRC Press – 23 oct 2023 69982 lei  6-8 săpt.

Preț: 69982 lei

Preț vechi: 85343 lei
-18%

Puncte Express: 1050
Preț estimativ în valută:
12378€ • 14470$ • 10761£

Carte tipărită la comandă

Livrare economică 07-21 martie

 Adaugă în coș

Wish list
Gift list
Am citit!
Adaugă în listă

Specificații

ISBN-13: 9781032471235
ISBN-10: 1032471239
Pagini: 242
Ilustrații: 3 Line drawings, black and white; 3 Illustrations, black and white
Dimensiuni: 178 x 254 x 14 mm
Greutate: 0.45 kg
Ediția:1
Editura: CRC Press
Colecția Chapman and Hall/CRC

Public țintă

Postgraduate and Undergraduate Advanced

Notă biografică

David A. Harville served for 10 years as a mathematical statistician in the Applied Mathematics Research Laboratory of the Aerospace Research Laboratories (at Wright-Patterson AFB, Ohio), for 20 years as a full professor in Iowa State University’s Department of Statistics (where he now has emeritus status), and 7 years as a research staff member of the Mathematical Sciences Department of IBM’s T.J. Watson Research Center. He has extensive experience in the area of linear statistical models, having taught (on numerous occasions) M.S. and Ph.D. level courses on that subject, having been the thesis advisor of 10 Ph.D. graduates, and having authored (or co-authored) 3 books and more than 80 research articles. His work has been recognized through his election as a Fellow of the American Statistical Association and of the Institute of Mathematical Statistics and as a member of the International Statistical Institute.

Cuprins

Part 1: Additional Topics  8. Constrained Linear Models and Related Topics  Part 2: Exercises and Solutions  2. Matrix Algebra: A Primer  3. Random Vectors and Matrices  4. The General Linear Model  5. Estimation and Prediction: Classical Approach  6. Some Relevant Distributions and Their Properties  7. Confidence Intervals (or Sets) and Tests of Hypotheses  8. Constrained Linear Models and Related Topics

Descriere

Linear Models and the Relevant Distributions and Matrix Algebra: A Unified Approach, Volume 2 covers several important topics that were not included in the first volume. The second volume complements the first, providing detailed solutions to the exercises in both volumes.

Recenzii

"The book presents procedures for making statistical inferences on the basis of the classical linear statistical model, and discusses the various properties of those procedures. Supporting material on matrix algebra and statistical distributions is interspersed with a discussion of relevant inferential procedures and their properties. The coverage ranges from MS-level to advanced researcher. In particular, the material in chapters 6-7 is not covered in an approachable manner in any other books, and greatly generalizes the traditional normal-based linear regression model to the elliptical distributions, thus greatly elucidating the advanced reader on just how far this class of models can be extended. Refreshingly, the material also goes beyond the classical 20th century coverage to include some 21st century topics like microarray (big) data analysis, and control of false discovery rates in large scale experiments…From the point of view of an advanced instructor and researcher on the subject, I very strongly recommend publication…Note that…this book provides the coverage of 3 books, hence the title purporting to provide a ‘unified approach’ (of 3 related subjects) is indeed accurate."
~Alex Trindade, Texas Tech University
"The book is very well written, with exceptional attention to details. It provides detailed derivations or proofs of almost all the results, and offers in-depth coverage of the topics discussed. Some of these materials (e.g., spherical/elliptical distributions) are hard to find from other sources. Anyone who is interested in linear models should benefit from reading this book and find it especially useful for a thorough understanding of the linear-model theory in a unified framework... The book is a delight to read."
~Huaiqing Wu, Iowa State University
"This book is useful in two ways: an excellent text book for a graduate level linear models course, and for those who want to learn linear models from a theoretical perspective…I genuinely enjoyed reading Ch 1and Ch 4 (Introduction and General Linear Models). Often, the hardest part of teaching linear models from a theoretical perspective is to motivate the students about the utility and generality of such models and the related theory. This book does an excellent job in this area, while presenting a solid theoretical foundation.”
~Arnab Maity, North Carolina State University